ARFBF MORPHOLOGICAL ANALYSIS - APPLICATION TO THE DISCRIMINATION OF CATALYST ACTIVE PHASES

Authors

  • Zhangyun Tan LISTIC EA 3703, University Savoie Mont Blanc
  • Maxime Moreaud IFP Energies nouvelles, rond-point de l’echangeur de Solaize, BP 3, 69360 Solaize
  • Olivier Alata Laboratoire Hubert Curien, CNRS UMR 5516, Jean Monnet University of Saint-Etienne
  • Abdourrahmane M. Atto LISTIC, EA 3703, University Savoie Mont Blanc

DOI:

https://doi.org/10.5566/ias.1624

Keywords:

auto-regressive field, fractional Brownian field, HRTEM imaging, mathematical morphology, texture analysis

Abstract

This paper addresses the characterization of spatial arrangements of fringes in catalysts imaged by High Resolution Transmission Electron Microscopy (HRTEM). It presents a statistical model-based approach for analyzing these fringes. The proposed approach involves Fractional Brownian Field (FBF) and 2-D AutoRegressive (AR) modeling, as well as morphological analysis. The originality of the approach consists in identifying the image background as an FBF, subtracting this background, modeling the residual by 2-D AR so as to capture fringe information and, finally, discriminating catalysts from fringe characterizations obtained by morphological analysis. The overall analysis is called ARFBF (Auto-Regressive Fractional Brownian Field) based morphology characterization. 

Author Biography

Maxime Moreaud, IFP Energies nouvelles, rond-point de l’echangeur de Solaize, BP 3, 69360 Solaize

Project leader

Image processing and analysis.

Control, Signal and System Department

Mechatronics, Computer Science and Applied Mathematics Division

 

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Published

2018-04-12

How to Cite

Tan, Z., Moreaud, M., Alata, O., & Atto, A. M. (2018). ARFBF MORPHOLOGICAL ANALYSIS - APPLICATION TO THE DISCRIMINATION OF CATALYST ACTIVE PHASES. Image Analysis and Stereology, 37(1), 21–34. https://doi.org/10.5566/ias.1624

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Original Research Paper